Identifying Predictors of Homelessness Among Adults in a Large Integrated Health System in Northern California.

ABSTRACT: Introduction Homelessness contributes to worsening health and increased health care costs. There is little published research that leverages rich electronic health record (EHR) data to predict future homelessness risk and inform interventions to address it. The authors' objective was to develop a model for predicting future homelessness using individual EHR and geographic data covariates. Methods This retrospective cohort study included 2,543,504 adult members (≥ 18 years old) from Kaiser Permanente Northern California and evaluated which covariates predicted a composite outcome of homelessness status (hospital discharge documentation of a homeless patient, medical diagnosis of homelessness, approved medical financial assistance application for homelessness, and/or "homeless/shelter" in ad

SUBMITTER: Rodriguez LA 

PROVIDER: S-EPMC10013725 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature